Impact of ‘Ideal Clinic’ implementation on patient waiting time in primary healthcare clinics in KwaZulu-Natal Province, South Africa: A before-and-after evaluation

Egbujie, Bonaventure Amandi; Grimwood, Ashraf; Mothibi-Wabafor, E C; Fatti, Geoffrey; Tshabalala, A M E T; Allie, Shaheema; Vilakazi, G; Oyebanji, Oyeronke

doi:10.7196/samj.2017.v108i4.12583

Cited by 19 publications

(18 citation statements)

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“…In this study, 70% of observed patients were at the PHC facilities for 3 h or more. The high median waiting time in our study was similar to the findings of Egbujie et al, which showed that some clinics in South Africa have reduced while others have increased waiting time after the implementation of the ICRM programme [60]. Observed inefficiencies in our study included excessive waiting time and nurses’ motion and rework.…”

Section: Discussionsupporting

confidence: 87%

Process evaluation of implementation fidelity of the integrated chronic disease management model in two districts, South Africa

Lebina

Alaba

Ringane

et al. 2019

BMC Health Serv Res

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BackgroundThe Integrated Chronic Disease Management (ICDM) model has been implemented in South Africa to enhance quality of clinical services in Primary Healthcare (PHC) clinics in a context of a high prevalence of chronic conditions and multi-morbidity. This study aimed to assess the implementation fidelity (adherence to guidelines) of the ICDM model.MethodsA cross-sectional study in 16 PHC clinics in two health districts in South Africa: Dr. Kenneth Kaunda (DKK) and West Rand (WR). A fidelity assessment tool with 89 activities and maximum score of 158 was developed from the four interrelated ICDM model components: facility re-organization, clinical supportive management, assisted self-management and strengthening of support systems. Value stream mapping of patient flow was conducted to analyse waiting time and identify operational inefficiencies. ICDM items were scored based on structured observations, facility document reviews and structured questionnaires completed by healthcare workers. Fidelity scores were summarized using medians and proportions and compared by facilities and districts using Chi-Square and Kruskal Wallis test.ResultsThe monthly patient headcount over a six-month period in these 16 PHC clinics was a median of 2430 (IQR: 1685–2942) individuals over 20 years. The DKK district had more newly diagnosed TB patients per month [median 5.5 (IQR: 4.00–9.33) vs 2.0 (IQR: 1.67–2.92)], and fewer medical officers per clinic [median 1 (IQR: 1–1) vs 3.5 (IQR:2–4.5)] compared to WR district. The median fidelity scores in both districts for facility re-organization, clinical supportive management, assisted self-management and strengthening of support systems were 78% [29/37, IQR: 27–31)]; 77% [30/39 (IQR: 27–34)]; 77% [30/39 (IQR: 28–34)]; and 80% [35/44 (IQR: 30–37)], respectively. The overall median implementation fidelity of the ICDM model was 79% (125/158, IQR, 117–132); WR was 80% (126/158, IQR, 123–132) while DKK was 74% (117/158, IQR, 106–130), p = 0.1409. The lowest clinic fidelity score was 66% (104/158), while the highest was 86% (136/158). A patient flow analysis showed long (2–5 h) waiting times and one stream of care for acute and chronic services.ConclusionThere was some variability of scores on components of the ICDM model by PHC clinics. More research is needed on contextual adaptations of the model.

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Section: Discussionsupporting

confidence: 87%

Process evaluation of implementation fidelity of the integrated chronic disease management model in two districts, South Africa

Lebina

Alaba

Ringane

et al. 2019

BMC Health Serv Res

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“…For example, South Africa has begun a nationwide Ideal Clinic programme and Tanzania has used a star-rating system to measure quality of primary care. 44 These results are being used to identify entry points for health-system improvement. Our analysis shows that at all levels of development and across different scopes of insured services, poor quality of care will limit the mortality reduction possible from greater coverage.…”

Section: Discussionmentioning

confidence: 99%

Mortality due to low-quality health systems in the universal health coverage era: a systematic analysis of amenable deaths in 137 countries

et al. 2018

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SummaryBackgroundUniversal health coverage has been proposed as a strategy to improve health in low-income and middle-income countries (LMICs). However, this is contingent on the provision of good-quality health care. We estimate the excess mortality for conditions targeted in the Sustainable Development Goals (SDG) that are amenable to health care and the portion of this excess mortality due to poor-quality care in 137 LMICs, in which excess mortality refers to deaths that could have been averted in settings with strong health systems.MethodsUsing data from the 2016 Global Burden of Disease study, we calculated mortality amenable to personal health care for 61 SDG conditions by comparing case fatality between each LMIC with corresponding numbers from 23 high-income reference countries with strong health systems. We used data on health-care utilisation from population surveys to separately estimate the portion of amenable mortality attributable to non-utilisation of health care versus that attributable to receipt of poor-quality care.Findings15·6 million excess deaths from 61 conditions occurred in LMICs in 2016. After excluding deaths that could be prevented through public health measures, 8·6 million excess deaths were amenable to health care of which 5·0 million were estimated to be due to receipt of poor-quality care and 3·6 million were due to non-utilisation of health care. Poor quality of health care was a major driver of excess mortality across conditions, from cardiovascular disease and injuries to neonatal and communicable disorders.InterpretationUniversal health coverage for SDG conditions could avert 8·6 million deaths per year but only if expansion of service coverage is accompanied by investments into high-quality health systems.FundingBill & Melinda Gates Foundation.

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“…Waiting times and long queues are the intense explanation for dissatisfaction for adolescents attending the public clinic in this study. (Egbujie et al, 2018) indicated that long waiting times are a major source of dissatisfaction for patients attending public healthcare facilities in South Africa. Patient load per nurse, kind of service received and time of arrival in facilities were all associated with waiting times.…”

Section: Discussionmentioning

confidence: 99%

Factors Contributing to Delayed Health Seeking Behaviours Among Adolescents

Mboweni¹,

Sumbane²

2019

GJHS

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BACKGROUND: Most adolescents for various reasons fail to go and seek for health care regarding health risks and challenges until they are faced with the complications. The socio-cultural belief concerning the causes of illnesses and its characteristic has correlation with the treatment seeking behaviour of an individual. OBJECTIVES: The study explored and described factors contributing to delayed health-seeking behaviours amongst adolescents in Kutlwanong clinic, North West Province. METHOD: This was a qualitative study designed using a phenomenological approach. Individual semi-structured in-depth interviews were audiotaped and transcribed verbatim. 8 Steps of Tesch’s inductive, descriptive open coding technique by Creswell was used followed by independent coding. Purposive sampling recruited fourteen participants aged 15–18 years. Trustworthiness criteria adhered to were credibility, dependability, transferability, and confirmability. Ethical clearance was sought with the University of Limpopo. RESULTS: Factors that negatively impact adolescents’ health-seeking behavior include the negative attitude of nurses and community, influenced by peers, shortage of medicine, lack of services throughout weekends, long queues, waiting times, distance, and lack of knowledge. Family planning and antenatal care were the common reason for seeking health care. CONCLUSION: Being aware of factors contributing to delay health-seeking behaviours will facilitate with setting future priorities to guard the health, well-being, and dignity of adolescents. The impacts of youth programs must be monitored on a regular basis to assess the needs and capabilities of specific facilities. Clinic manager to ensure compliance with the national core standards to meet adolescent’s immediate expectations.

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Impact of ‘Ideal Clinic’ implementation on patient waiting time in primary healthcare clinics in KwaZulu-Natal Province, South Africa: A before-and-after evaluation

Cited by 19 publications

References 0 publications

Process evaluation of implementation fidelity of the integrated chronic disease management model in two districts, South Africa

Process evaluation of implementation fidelity of the integrated chronic disease management model in two districts, South Africa

Mortality due to low-quality health systems in the universal health coverage era: a systematic analysis of amenable deaths in 137 countries

Factors Contributing to Delayed Health Seeking Behaviours Among Adolescents

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